Comprehensive Analysis of Transcriptome Variation Uncovers Known and Novel Driver Events in T-Cell Acute Lymphoblastic Leukemia

Rna-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (snv),while simultaneously obtaining information on structural variations and gene expression perturbations. we asked whether rna-seq is suitable for the detection of driver mutations in t-cell acute lymphoblastic leukemia (t-all). these leukemias are caused by a combination of gene fusions,over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. we analyzed 31 t-all patient samples and 18 t-all cell lines by high-coverage paired-end rna-seq. first,we optimized the detection of snvs in rna-seq data by comparing the results with exome re-sequencing data. we identified known driver genes with recurrent protein altering variations,as well as several new candidates including h3f3a,ptk2b,and stat5b. next,we determined accurate gene expression levels from the rna-seq data through normalizations and batch effect removal,and used these to classify patients into t-all subtypes. finally,we detected gene fusions,of which several can explain the over-expression of key driver genes such as tlx1,plag1,lmo1,or nkx2-1; and others result in novel fusion transcripts encoding activated kinases (ssbp2-fer and tpm3-jak2) or involving mllt10. in conclusion,we present novel analysis pipelines for variant calling,variant filtering,and expression normalization on rna-seq data,and successfully applied these for the detection of translocations,point mutations,indels,exon-skipping events,and expression perturbations in t-all. © 2013 kalender atak et al.